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Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal Pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin Singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

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Unbiased Parameter Estimation for Partially Observed Diffusions

arXiv

引用

arXiv 2023年

作者： Awadelkarim, Elsiddig Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular, we assume that one must time-discretize the partially observed diffusion process and work with the model with bias and consider maximizing the resulting log-likelihood. Using a novel double randomization scheme, based upon Markovian stochastic approximation we develop a new method to unbiasedly estimate the static parameters, that is, to obtain the maximum likelihood estimator with no time discretization bias. Under assumptions we prove that our estimator is unbiased and investigate the method in several numerical examples, showing that it can empirically out-perform existing unbiased *** Codes 60J22, 62M05, 65C40, 62M20 © 2023, CC BY.

关键词： Parameter estimation

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Low-temperature spin Seebeck effect in nonmagnetic vanadium dioxide

引用

Physical Review B 2024年第2期110卷 024415-024415页

作者： Renjie Luo Tanner J. Legvold Liyang Chen Henry Navarro Ali C. Basaran Deshun Hong Changjiang Liu Anand Bhattacharya Ivan K. Schuller Douglas Natelson Department of Physics and Astronomy Applied Physics Graduate Program Rice Quantum Institute Department of Physics and Center for Advanced Nanoscience Materials Science Division Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low-temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature-dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination.

关键词： Spin Seebeck effect Paramagnets Strongly correlated systems

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Day-Ahead Forecasting of Solar Irradiance & PV Power Output Through Statistical Machine Learning Methods

Day-Ahead Forecasting of Solar Irradiance & PV Power Output ...

引用

2022 Saudi Arabia Smart Grid Conference, SASG 2022

作者： Kamarianakis, Yiannis Pantazis, Yannis Kalligiannaki, Evangelia Katsaounis, Theodoros D. Kotsovos, Konstantinos Gereige, Issam Abdullah, Marwan Jamal, Aqil Tzavaras, Athanasios Foundation for Research and Technology-Hellas Institute of Applied and Computational Mathematics Data Science Group Greece University of Crete Dept. of Mathematics and Applied Mathematics Greece Saudi Aramco RandD Center Carbon Management Division Dhahran Saudi Arabia Computer Electrical and Mathematical Sciences and Engineering Division Thuwal Saudi Arabia

ISBN: (纸本)9781665475891

Energy production from solar photovoltaic (PV) plants is unpredictable, mainly due to the stochastic formation and movement of clouds or aerosol - dust particles which scatter or disperse solar radiation. Accurate forecasts of PV output are essential to Distribution and Transportation System Operators as they assist efficient solar energy trading and management of electricity grids. This work evaluates an autoregressive, computationally-light KNN-regression scheme (TSFKNN) for hourly, day-ahead forecasts of solar irradiance and energy yield of various PV technologies. The model is being tested and validated using data measured in Thuwal, Saudi Arabia. The available measured records span a 60-month period. The developed forecasting models are designed for online systems and provide increased levels of accuracy and low computational cost. Several parametric and nonparametric specifications, coupled with conventional versus outlier-robust estimation procedures are tested, in order to derive an optimal month-specific daily profile (MDP). Current results demonstrate that including intraday variability to the monthly-based irradiance models achieve improved predictive accuracy between 10% and 25% on average. © 2022 IEEE.

关键词： Forecasting

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Antithetic Multilevel Particle Filters

arXiv

引用

arXiv 2023年

作者： Jasra, Ajay Maama, Mohamed Ombao, Hernando Applied Mathematics and Computational Science Program United States Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. This is a challenging problem which requires the use of advanced numerical schemes based upon time-discretization of the diffusion process and then the application of particle filters. Perhaps the state-of-the-art method for moderate dimensional problems is the multilevel particle filter of [12]. This is a method that combines multilevel Monte Carlo and particle filters. The approach in that article is based intrinsically upon an Euler discretization method. We develop a new particle filter based upon the antithetic truncated Milstein scheme of [10]. We show that for a class of diffusion problems, for ϵ > 0 given, that the cost to produce a mean square error (MSE) in estimation of the filter, of O(ϵ2) is O(ϵ−2 log(ϵ)2). In the case of multidimensional diffusions with non-constant diffusion coefficient, the method of [12] has a cost of O(ϵ−2.5) to achieve the same MSE. We support our theory with numerical results in several examples. Copyright © 2023, The Authors. All rights reserved.

关键词： Mean square error

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Accounting for deficit and a known demand quantile in ABC-XYZ analysis 6

Accounting for deficit and a known demand quantile in ABC-XY...

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6th IEEE International Conference on Logistics Operations Management, GOL 2022

作者： Zenkova, Zhanna Andrievskaya, Anna Tarima, Sergey Institute of Applied Mathematics and Computer Science Tomsk State University Tomsk Russia Institute for Health and Equity Medical College of Wisconsin Division of Biostatistics Milwaukee United States

ISBN: (纸本)9781665469326

Product deficit typically appears as a result of inadequate planning and unforeseen supply chain disruptions. A traditional approach to demand distribution estimation does not account for possible deficit;deficit generates right censored data. If the censoring is ignored, the demand estimation becomes negatively biased. Consequently, all analytics based on the demand distribution also becomes biased. In this article, the well-known survival analysis Kaplan-Meier estimator is applied to demand data with observed deficit. In addition to the reduction of bias associated with the use of the KaplanMeier estimator, we also modify it with a known quantile of the demand distribution. Monte-Carlo simulation studies show that the use of additional information in the presence of censored observations substantially improves estimation quality. The estimators modified with quantile information led to new product grouping in the ABC-XYZ analysis. An illustrative example shows the impact of new estimators on ABC-XYZ grouping. © 2022 IEEE.

关键词： Monte Carlo methods

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Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

引用

npj Computational Materials 2023年第1期9卷 733-743页

作者： Evan R.Antoniuk Gowoon Cheon George Wang Daniel Bernstein William Cai Evan J.Reed Materials Science Division Physical and Life Sciences DirectorateLawrence Livermore National LaboratoryLivermoreCAUSA Department of Chemistry Stanford UniversityStanfordCAUSA Department of Applied Physics Stanford UniversityStanfordCAUSA Google Research Mountain ViewCAUSA Department of Physics Stanford UniversityStanfordCAUSA Department of Mathematics Stanford UniversityStanfordCAUSA Department of Computer Science Stanford UniversityStanfordCAUSA Department of Materials Science and Engineering Stanford UniversityStanfordCAUSA

Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials *** this work,we develop a deep learning synthesizability model(SynthNN)that leverages the entire space of synthesized inorganic chemical *** reformulating material discovery as a synthesizability classification task,SynthNN identifies synthesizable materials with 7×higher precision than with DFT-calculated formation *** a head-to-head material discovery comparison against 20 expert material scientists,SynthNN outperforms all experts,achieves 1.5×higher precision and completes the task five orders of magnitude faster than the best human ***,without any prior chemical knowledge,our experiments indicate that SynthNN learns the chemical principles of charge-balancing,chemical family relationships and ionicity,and utilizes these principles to generate synthesizability *** development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

关键词： inorganic crystalline utilize

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Stochastic Dynamics and Probability Analysis for a Generalized Epidemic Model with Environmental Noise

arXiv

引用

arXiv 2024年

作者： Boukanjime, Brahim Maama, Mohamed Laboratory of Mathematical Modeling and Economic Calculations Hassan First University of Settat Morocco Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia

In this paper we consider a stochastic SEIQR (susceptible-exposed-infected-quarantined-recovered) epidemic model with a generalized incidence function. Using the Lyapunov method, we establish the existence and uniqueness of a global positive solution to the model, ensuring that it remains well-defined over time. Through the application of Young’s inequality and Chebyshev’s inequality, we demonstrate the concepts of stochastic ultimate boundedness and stochastic permanence, providing insights into the long-term behavior of the epidemic dynamics under random perturbations. Furthermore, we derive conditions for stochastic extinction, which describes scenarios where the epidemic may eventually die out, and V-geometric ergodicity, which indicates the rate at which the system’s state converges to its equilibrium. Finally, we perform numerical simulations to verify our theoretical results and assess the model’s behavior under different parameters. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic models

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Optimizing Insurance Strategies through Disaster Risk Assessment Models: A Case Study of Earthquakes in Japan

Optimizing Insurance Strategies through Disaster Risk Assess...

引用

Computing Innovation, Intelligence, Technologies and Education (CIITE), International Conference on

作者： Qiyuan Luo Xingnan Zhang Yuanxin Zhang Burra Venkata Durga Kumar Meifeng Liu Program in Computer Science & Technology Xiamen University Malaysia Kuala Lumplur Malaysia Program in Software Engineering Xiamen University Malaysia Kuala Lumplur Malaysia Program in Mathematics and Applied Mathematics Xiamen University Malaysia Kuala Lumplur Malaysia

ISBN: (数字)9798350377286

ISBN: (纸本)9798350377293

With the increasing frequency of extreme weather events and natural disasters, insurance providers around the world are facing enormous challenges. This study addresses insurance claims resulting from these disasters by developing a comprehensive disaster insurance risk assessment model, focusing on Japan, a country prone to frequent earthquakes. The model integrates a Catastrophe Model, the Analytic Hierarchy Process (AHP), and an expert scoring method to optimize the risk assessment and compensation process for historic buildings. The results show that the model has strong predictive power, which provides valuable insights for insurance companies, policymakers, and urban planners in mitigating the impact of disasters and protecting cultural heritage.

关键词： Analytical models Disasters Earthquakes Buildings Insurance Predictive models Risk management Cultural differences Meteorology Context modeling

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Multilevel Particle Filters for Partially Observed McKean-Vlasov Stochastic Differential Equations

arXiv

引用

arXiv 2024年

作者： Awadelkarim, Elsiddig Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia School of Data Science The Chinese University of Hong Kong Shenzhen China

In this paper we consider the filtering problem associated to partially observed McKean-Vlasov stochastic differential equations (SDEs). The model consists of data that are observed at regular and discrete times and the objective is to compute the conditional expectation of (functionals) of the solutions of the SDE at the current time. This problem, even the ordinary SDE case is challenging and requires numerical approximations. Based upon the ideas in [3, 12] we develop a new particle filter (PF) and multilevel particle filter (MLPF) to approximate the afore-mentioned expectations. We prove under assumptions that, for ϵ > 0, to obtain a mean square error of O(ϵ2) the PF has a cost per-observation time of O(ϵ−5) and the MLPF costs O(ϵ−4) (best case) or O(ϵ−4 log(ϵ)2) (worst case). Our theoretical results are supported by numerical experiments. © 2024, CC BY.

关键词： Mean square error

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